Automatic generation of primary sequence patterns from sets of related protein sequences.
We have developed a computer algorithm that can extract the pattern of conserved primary sequence elements common to all members of a homologous protein family. The method involves clustering the pairwise similarity scores among a set of related sequences to generate a binary dendrogram (tree). The tree is then reduced in a stepwise manner by progressively replacing the node connecting the two most similar termini by one common pattern until only a single common "root" pattern remains. A pattern is generated at a node by (i) performing a local optimal alignment on the sequence/pattern pair connected by the node with the use of an extended dynamic programming algorithm and then (ii) constructing a single common pattern from this alignment with a nested hierarchy of amino acid classes to identify the minimal inclusive amino acid class covering each paired set of elements in the alignment. Gaps within an alignment are created and/or extended using a "pay once" gap penalty rule, and gapped positions are converted into gap characters that function as 0 or 1 amino acid of any type during subsequent alignment. This method has been used to generate a library of covering patterns for homologous families in the National Biomedical Research Foundation/Protein Identification Resource protein sequence data base. We show that a covering pattern can be more diagnostic for sequence family membership than any of the individual sequences used to construct the pattern.
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Department of Biostatistics, Dana-Farber Cancer Institute, Boston, MA 02115.
Smith
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D000595:Amino Acid Sequence; D001483:Base Sequence; D008433:Mathematics; D008962:Models, Theoretical; D008969:Molecular Sequence Data; D011506:Proteins / Q000235:genetics*; D012689:Sequence Homology, Nucleic Acid; D012697:Serine Endopeptidases / Q000235:genetics; D014362:Trypsinogen / Q000235:genetics
D011506:Proteins; D014362:Trypsinogen; D012697:Serine Endopeptidases